How to Detect Linear Dependence on the Copula Level?

Authors

Vladik Kreinovich, The University of Texas at El PasoFollow
Hung T. Nguyen, New Mexico State University - Main CampusFollow
Songsak Sriboonchitta, Chiang Mai UniversityFollow

Publication Date

7-2013

Comments

Technical Report: UTEP-CS-13-36a

Abstract

In many practical situations, the dependence between the quantities is linear or approximately linear. Knowing that the dependence is linear simplifies computations; so, is is desirable to detect linear dependencies. If we know the joint probability distribution, we can detect linear dependence by computing Pearson's correlation coefficient. In practice, we often have a copula instead of a full distribution; in this case, we face a problem of detecting linear dependence based on the copula. Also, distributions are often heavy-tailed, with infinite variances, in which case Pearson's formulas cannot be applied. In this paper, we show how to modify Pearson's formula so that it can be applied to copulas and to heavy-tailed distributions.